DA4507 FRM curriculum updates part II

PART
II
FRM
2019 CURRICULUM UPDATES


GARP updates the program curriculum every year
to ensure study materials and exams reflect the most
up-to-date knowledge and skills required to be
successful as a risk professional.
See updates to the 2019 PART II FRM program curriculum.


MR-1

2018

Kevin Dowd, Measuring Market Risk, 2nd Edition
(West Sussex, England: John Wiley & Sons, 2005).
Chapter 3. Estimating Market Risk Measures:
An Introduction and Overview

MR-1

2019

Kevin Dowd, Measuring Market Risk, 2nd Edition
(West Sussex, England: John Wiley & Sons, 2005).
Chapter 3. Estimating Market Risk Measures:
An Introduction and Overview

• Estimate VaR using a historical simulation approach.

• Estimate VaR using a historical simulation approach.

• Estimate VaR using a parametric approach for both normal and
lognormal return distributions.

• Estimate VaR using a parametric approach for both normal and
lognormal return distributions.

• Estimate the expected shortfall given P/L or return data.

• Estimate the expected shortfall given P/L or return data.

• Define coherent risk measures.

• Define coherent risk measures.

• Estimate risk measures by estimating quantiles.

• Estimate risk measures by estimating quantiles.

• Evaluate estimators of risk measures by estimating their standard
errors.

• Evaluate estimators of risk measures by estimating their standard
errors.

• Interpret QQ plots to identify the characteristics of a distribution.

• Interpret QQ plots to identify the characteristics of a distribution.

NO CHANGES


MR-2

2018

MR-2

2019

Kevin Dowd, Measuring Market Risk, 2nd Edition
(West Sussex, England: John Wiley & Sons, 2005).
Chapter 4. Non-parametric Approaches

Kevin Dowd, Measuring Market Risk, 2nd Edition
(West Sussex, England: John Wiley & Sons, 2005).
Chapter 4. Non-parametric Approaches

• Apply the bootstrap historical simulation approach to estimate
coherent risk measures.

• Apply the bootstrap historical simulation approach to estimate
coherent risk measures.

• Describe historical simulation using non-parametric density
estimation.

• Describe historical simulation using non-parametric density
estimation.

• Compare and contrast the age-weighted, the volatility-weighted,
the correlation-weighted and the filtered historical simulation
approaches.

• Compare and contrast the age-weighted, the volatility-weighted,
the correlation-weighted and the filtered historical simulation
approaches.

• Identify advantages and disadvantages of non-parametric
estimation methods.

• Identify advantages and disadvantages of non-parametric
estimation methods.

NO CHANGES


MR-3

2018

Philippe Jorion, Value-at-Risk:
The New Benchmark for Managing Financial Risk,
3rd Edition (New York: McGraw-Hill, 2007).
Chapter 6. Backtesting VaR

MR-3

2019

Philippe Jorion, Value-at-Risk:
The New Benchmark for Managing Financial Risk,
3rd Edition (New York: McGraw-Hill, 2007).
Chapter 6. Backtesting VaR

• Define backtesting and exceptions and explain the importance of
backtesting VaR models.

• Define backtesting and exceptions and explain the importance of
backtesting VaR models.

• Explain the significant difficulties in backtesting a VaR model.

• Explain the significant difficulties in backtesting a VaR model.

• Verify a model based on exceptions or failure rates.

• Verify a model based on exceptions or failure rates.

• Define and identify type I and type II errors.

• Define and identify type I and type II errors.

• Explain the need to consider conditional coverage in the backtesting
framework.

• Explain the need to consider conditional coverage in the backtesting

framework.

• Describe the Basel rules for backtesting.

• Describe the Basel rules for backtesting.

NO CHANGES


MR-4

2018

Philippe Jorion, Value-at-Risk:
The New Benchmark for Managing Financial Risk,
3rd Edition (New York: McGraw-Hill, 2007).
Chapter 11. VaR Mapping

MR-4

2019

Philippe Jorion, Value-at-Risk:
The New Benchmark for Managing Financial Risk,
3rd Edition (New York: McGraw-Hill, 2007).
Chapter 11. VaR Mapping

• Explain the principles underlying VaR mapping, and describe the
mapping process.

• Explain the principles underlying VaR mapping, and describe the
mapping process.

• Explain how the mapping process captures general and specific
risks.

• Explain how the mapping process captures general and specific
risks.

• Differentiate among the three methods of mapping portfolios of
fixed income securities.

• Differentiate among the three methods of mapping portfolios of
fixed income securities.

• Summarize how to map a fixed income portfolio into positions of
standard instruments.

• Summarize how to map a fixed income portfolio into positions of
standard instruments.

• Describe how mapping of risk factors can support stress testing.

• Describe how mapping of risk factors can support stress testing.

• Explain how VaR can be used as a performance benchmark.

• Explain how VaR can be used as a performance benchmark.

• Describe the method of mapping forwards, forward rate

agreements, interest rate swaps, and options.

• Describe the method of mapping forwards, forward rate
agreements, interest rate swaps, and options.

NO CHANGES


MR-5

2018

Messages from the academic literature on
risk measurement for the trading book,
Basel Committee on Banking Supervision,
Working Paper No. 19, Jan 2011.

MR-5

2019

Messages from the academic literature on
risk measurement for the trading book,
Basel Committee on Banking Supervision,
Working Paper No. 19, Jan 2011.

• Explain the following lessons on VaR implementation: time horizon
over which VaR is estimated, the recognition of time varying
volatility in VaR risk factors, and VaR backtesting.

• Explain the following lessons on VaR implementation: time horizon
over which VaR is estimated, the recognition of time varying
volatility in VaR risk factors, and VaR backtesting.

• Describe exogenous and endogenous liquidity risk and explain how
they might be integrated into VaR models.

• Describe exogenous and endogenous liquidity risk and explain how
they might be integrated into VaR models.

• Compare VaR, expected shortfall, and other relevant risk measures.

• Compare VaR, expected shortfall, and other relevant risk measures.

• Compare unified and compartmentalized risk measurement.

• Compare unified and compartmentalized risk measurement.

• Compare the results of research on “top-down” and “bottom-up”
risk aggregation methods.

• Compare the results of research on “top-down” and “bottom-up”
risk aggregation methods.

• Describe the relationship between leverage, market value of asset,
and VaR within an active balance sheet management framework.

• Describe the relationship between leverage, market value of asset,
and VaR within an active balance sheet management framework.

NO CHANGES


MR-6

2018

MR-6

2019

Gunter Meissner, Correlation Risk Modeling and
Management (New York: John Wiley & Sons, 2014).
Chapter 1. Some Correlation Basics: Properties,
Motivation, Terminology

Gunter Meissner, Correlation Risk Modeling and
Management (New York: John Wiley & Sons, 2014).
Chapter 1. Some Correlation Basics: Properties,
Motivation, Terminology

• Describe financial correlation risk and the areas in which it appears
in finance.

• Describe financial correlation risk and the areas in which it appears
in finance.

• Explain how correlation contributed to the global financial crisis of
2007 to 2009.

• Explain how correlation contributed to the global financial crisis of
2007 to 2009.

• Describe the structure, uses, and payoffs of a correlation swap.

• Describe the structure, uses, and payoffs of a correlation swap.

• Estimate the impact of different correlations between assets in the
trading book on the VaR capital charge.

• Estimate the impact of different correlations between assets in the
trading book on the VaR capital charge.

• Explain the role of correlation risk in market risk and credit risk.

• Explain the role of correlation risk in market risk and credit risk.

• Relate correlation risk to systemic and concentration risk.

• Relate correlation risk to systemic and concentration risk.

NO CHANGES


MR-7

2018

MR-7

2019

Gunter Meissner, Correlation Risk Modeling and
Management (New York: John Wiley & Sons, 2014).
Chapter 2. Empirical Properties of Correlation:
How Do Correlations Behave in the Real World?

Gunter Meissner, Correlation Risk Modeling and
Management (New York: John Wiley & Sons, 2014).
Chapter 2. Empirical Properties of Correlation:
How Do Correlations Behave in the Real World?

• Describe how equity correlations and correlation volatilities behave
throughout various economic states.

• Describe how equity correlations and correlation volatilities behave
throughout various economic states.

• Calculate a mean reversion rate using standard regression and
calculate the corresponding autocorrelation.

• Calculate a mean reversion rate using standard regression and
calculate the corresponding autocorrelation.

• Identify the best-fit distribution for equity, bond, and default
correlations

• Identify the best-fit distribution for equity, bond, and default
correlations

NO CHANGES


MR-8

2018

Gunter Meissner, Correlation Risk Modeling and
Management (New York: John Wiley & Sons, 2014).
Chapter 3. Statistical Correlation Models—
Can We Apply Them to Finance?

MR-8

2019

Gunter Meissner, Correlation Risk Modeling and
Management (New York: John Wiley & Sons, 2014).
Chapter 3. Statistical Correlation Models—
Can We Apply Them to Finance?

• Evaluate the limitations of financial modeling with respect to the
model itself, calibration of the model, and the model’s output.

• Evaluate the limitations of financial modeling with respect to the
model itself, calibration of the model, and the model’s output.

• Assess the Pearson correlation approach, Spearman’s rank
correlation, and Kendall’s τ, and evaluate their limitations and
usefulness in finance.

• Assess the Pearson correlation approach, Spearman’s rank
correlation, and Kendall’s τ, and evaluate their limitations and
usefulness in finance.

NO CHANGES


MR-9

2018

Gunter Meissner, Correlation Risk Modeling and
Management (New York: John Wiley & Sons, 2014).
Chapter 4. Financial Correlation Modeling—Bottom-Up
Approaches (Sections 4.3.0 (intro), 4.3.1, and 4.3.2 only)

MR-9

2019

Gunter Meissner, Correlation Risk Modeling and
Management (New York: John Wiley & Sons, 2014).
Chapter 4. Financial Correlation Modeling—Bottom-Up
Approaches (Sections 4.3.0 (intro), 4.3.1, and 4.3.2 only)

• Explain the purpose of copula functions and the translation of the
copula equation.

• Explain the purpose of copula functions and the translation of the

copula equation.

• Describe the Gaussian copula and explain how to use it to derive the
joint probability of default of two assets.

• Describe the Gaussian copula and explain how to use it to derive the
joint probability of default of two assets.

• Summarize the process of finding the default time of an asset
correlated to all other assets in a portfolio using the Gaussian
copula.

• Summarize the process of finding the default time of an asset
correlated to all other assets in a portfolio using the Gaussian
copula.

NO CHANGES


MR-10

2018

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 6. Empirical Approaches to
Risk Metrics and Hedging

MR-10

2019

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 6. Empirical Approaches to
Risk Metrics and Hedging

• Explain the drawbacks to using a DV01-neutral hedge for a bond
position.

• Explain the drawbacks to using a DV01-neutral hedge for a bond
position.

• Describe a regression hedge and explain how it can improve a
standard DV01-neutral hedge.

• Describe a regression hedge and explain how it can improve a
standard DV01-neutral hedge.

• Calculate the regression hedge adjustment factor, beta.

• Calculate the regression hedge adjustment factor, beta.

• Calculate the face value of an offsetting position needed to carry out
a regression hedge.

• Calculate the face value of an offsetting position needed to carry out
a regression hedge.

• Calculate the face value of multiple offsetting swap positions

needed to carry out a two-variable regression hedge.

• Calculate the face value of multiple offsetting swap positions
needed to carry out a two-variable regression hedge.

• Compare and contrast level and change regressions.

• Compare and contrast level and change regressions.

• Describe principal component analysis and explain how it is applied
to constructing a hedging portfolio.

• Describe principal component analysis and explain how it is applied
to constructing a hedging portfolio.

NO CHANGES


MR-11

2018

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 7. The Science of Term Structure Models

MR-11

2019

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 7. The Science of Term Structure Models

• Calculate the expected discounted value of a zero-coupon security
using a binomial tree.

• Calculate the expected discounted value of a zero-coupon security
using a binomial tree.

• Construct and apply an arbitrage argument to price a call option on
a zero-coupon security using replicating portfolios.

• Construct and apply an arbitrage argument to price a call option on
a zero-coupon security using replicating portfolios.

• Define risk-neutral pricing and apply it to option pricing.

• Define risk-neutral pricing and apply it to option pricing.

• Distinguish between true and risk-neutral probabilities, and apply
this difference to interest rate drift.

• Distinguish between true and risk-neutral probabilities, and apply
this difference to interest rate drift.

• Explain how the principles of arbitrage pricing of derivatives on
fixed income securities can be extended over multiple periods.

• Explain how the principles of arbitrage pricing of derivatives on

fixed income securities can be extended over multiple periods.

• Define option-adjusted spread (OAS) and apply it to security pricing.

• Define option-adjusted spread (OAS) and apply it to security pricing.

• Describe the rationale behind the use of recombining trees in option
pricing.

• Describe the rationale behind the use of recombining trees in option
pricing.

• Calculate the value of a constant maturity Treasury swap, given an
interest rate tree and the risk-neutral probabilities.

• Calculate the value of a constant maturity Treasury swap, given an
interest rate tree and the risk-neutral probabilities.

• Evaluate the advantages and disadvantages of reducing the size
of the time steps on the pricing of derivatives on fixed income
securities.

• Evaluate the advantages and disadvantages of reducing the size
of the time steps on the pricing of derivatives on fixed income
securities.

• Evaluate the appropriateness of the Black-Scholes-Merton model
when valuing derivatives on fixed income securities.

• Evaluate the appropriateness of the Black-Scholes-Merton model

when valuing derivatives on fixed income securities.

• Describe the impact of embedded options on the value of fixed
income securities.

• Describe the impact of embedded options on the value of fixed
income securities.

NO CHANGES


MR-12

2018

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 8. The Evolution of Short Rates and the
Shape of the Term Structure

MR-12

2019

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 8. The Evolution of Short Rates and the
Shape of the Term Structure

• Explain the role of interest rate expectations in determining the

shape of the term structure.

• Explain the role of interest rate expectations in determining the
shape of the term structure.

• Apply a risk-neutral interest rate tree to assess the effect of volatility
on the shape of the term structure.

• Apply a risk-neutral interest rate tree to assess the effect of volatility
on the shape of the term structure.

• Estimate the convexity effect using Jensen’s inequality.

• Estimate the convexity effect using Jensen’s inequality.

• Evaluate the impact of changes in maturity, yield and volatility on
the convexity of a security.

• Evaluate the impact of changes in maturity, yield and volatility on
the convexity of a security.

• Calculate the price and return of a zero coupon bond incorporating a
risk premium.

• Calculate the price and return of a zero coupon bond incorporating a
risk premium.

NO CHANGES

MR-13

2018

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 9. The Art of Term Structure Models: Drift

MR-13

2019

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 9. The Art of Term Structure Models: Drift

• Construct and describe the effectiveness of a short term interest
rate tree assuming normally distributed rates, both with and
without drift.

• Construct and describe the effectiveness of a short term interest
rate tree assuming normally distributed rates, both with and
without drift.

• Calculate the short-term rate change and standard deviation of the
rate change using a model with normally distributed rates and no
drift.

• Calculate the short-term rate change and standard deviation of the
rate change using a model with normally distributed rates and no

drift.

• Describe methods for addressing the possibility of negative shortterm rates in term structure models.

• Describe methods for addressing the possibility of negative shortterm rates in term structure models.

• Construct a short-term rate tree under the Ho-Lee Model with timedependent drift.

• Construct a short-term rate tree under the Ho-Lee Model with timedependent drift.

• Describe uses and benefits of the arbitrage-free models and assess
the issue of fitting models to market prices.

• Describe uses and benefits of the arbitrage-free models and assess
the issue of fitting models to market prices.

• Describe the process of constructing a simple and recombining tree
for a short-term rate under the Vasicek Model with mean reversion.

• Describe the process of constructing a simple and recombining tree
for a short-term rate under the Vasicek Model with mean reversion.

• Calculate the Vasicek Model rate change, standard deviation of the
rate change, expected rate in T years, and half-life.

• Calculate the Vasicek Model rate change, standard deviation of the
rate change, expected rate in T years, and half-life.

• Describe the effectiveness of the Vasicek Model.

• Describe the effectiveness of the Vasicek Model.

NO CHANGES


MR-14

2018

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 10. The Art of Term Structure Models:
Volatility and Distribution

MR-14

2019

Bruce Tuckman, Fixed Income Securities, 3rd Edition
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 10. The Art of Term Structure Models:
Volatility and Distribution

• Describe the short-term rate process under a model with timedependent volatility.

• Describe the short-term rate process under a model with timedependent volatility.

• Calculate the short-term rate change and determine the behavior of
the standard deviation of the rate change using a model with time
dependent volatility.

• Calculate the short-term rate change and determine the behavior of
the standard deviation of the rate change using a model with time
dependent volatility.

• Assess the efficacy of time-dependent volatility models.

• Assess the efficacy of time-dependent volatility models.

• Describe the short-term rate process under the Cox-Ingersoll-Ross
(CIR) and lognormal models.

• Describe the short-term rate process under the Cox-Ingersoll-Ross
(CIR) and lognormal models.

• Calculate the short-term rate change and describe the basis point
volatility using the CIR and lognormal models.

• Calculate the short-term rate change and describe the basis point
volatility using the CIR and lognormal models.

• Describe lognormal models with deterministic drift and mean
reversion.

• Describe lognormal models with deterministic drift and mean
reversion.

NO CHANGES

MR-16 MR-15

2018

New Edition: John C. Hull,
Options, Futures, and Other Derivatives, 10th Edition
(New York: Pearson, 2017). Chapter 20

MR-15

2019

New Edition: John C. Hull,
Options, Futures, and Other Derivatives, 10th Edition
(New York: Pearson, 2017). Chapter 20

• Define volatility smile and volatility skew.

• Define volatility smile and volatility skew.

• Explain the implications of put-call parity on the implied volatility of
call and put options.

• Explain the implications of put-call parity on the implied volatility of
call and put options.

• Compare the shape of the volatility smile (or skew) to the shape
of the implied distribution of the underlying asset price and to the
pricing of options on the underlying asset.

• Compare the shape of the volatility smile (or skew) to the shape
of the implied distribution of the underlying asset price and to the
pricing of options on the underlying asset.

• Describe characteristics of foreign exchange rate distributions and
their implications on option prices and implied volatility.

• Describe characteristics of foreign exchange rate distributions and
their implications on option prices and implied volatility.

• Describe the volatility smile for equity options and foreign currency
options and provide possible explanations for its shape.

• Describe the volatility smile for equity options and foreign currency
options and provide possible explanations for its shape.

• Describe alternative ways of characterizing the volatility smile.

• Describe alternative ways of characterizing the volatility smile.

• Describe volatility term structures and volatility surfaces and how
they may be used to price options.

• Describe volatility term structures and volatility surfaces and how
they may be used to price options.

• Explain the impact of the volatility smile on the calculation of the
“Greeks.”

• Explain the impact of the volatility smile on the calculation of the

“Greeks.”

• Explain the impact of a single asset price jump on a volatility smile.

• Explain the impact of a single asset price jump on a volatility smile.

NO CHANGES


CR-1

2018

Jonathan Golin and Philippe Delhaise,
The Bank Credit Analysis Handbook, 2nd Edition
(Hoboken, NJ: John Wiley & Sons, 2013).
Chapter 1. The Credit Decision

CR-1

2019

Jonathan Golin and Philippe Delhaise,
The Bank Credit Analysis Handbook, 2nd Edition
(Hoboken, NJ: John Wiley & Sons, 2013).
Chapter 1. The Credit Decision

• Define credit risk and explain how it arises using examples.

• Define credit risk and explain how it arises using examples.

• Explain the components of credit risk evaluation.

• Explain the components of credit risk evaluation.

• Describe, compare and contrast various credit risk mitigants and
their role in credit analysis.

• Describe, compare and contrast various credit risk mitigants and
their role in credit analysis.

• Compare and contrast quantitative and qualitative techniques of
credit risk evaluation.

• Compare and contrast quantitative and qualitative techniques of
credit risk evaluation.

• Compare the credit analysis of consumers, corporations, financial
institutions, and sovereigns.

• Compare the credit analysis of consumers, corporations, financial
institutions, and sovereigns.

• Describe quantitative measurements and factors of credit risk,
including probability of default, loss given default, exposure at
default, expected loss, and time horizon.

• Describe quantitative measurements and factors of credit risk,
including probability of default, loss given default, exposure at
default, expected loss, and time horizon.

• Compare bank failure and bank insolvency.

• Compare bank failure and bank insolvency.

NO CHANGES


CR-2

2018

Jonathan Golin and Philippe Delhaise,
The Bank Credit Analysis Handbook, 2nd Edition
(Hoboken, NJ: John Wiley & Sons, 2013).
Chapter 2. The Credit Analyst

CR-2

2019

Jonathan Golin and Philippe Delhaise,
The Bank Credit Analysis Handbook, 2nd Edition
(Hoboken, NJ: John Wiley & Sons, 2013).
Chapter 2. The Credit Analyst

• Describe, compare and contrast various credit analyst roles.

• Describe, compare and contrast various credit analyst roles.

• Describe common tasks performed by a banking credit analyst.

• Describe common tasks performed by a banking credit analyst.

• Describe the quantitative, qualitative, and research skills a banking
credit analyst is expected to have.

• Describe the quantitative, qualitative, and research skills a banking
credit analyst is expected to have.

• Assess the quality of various sources of information used by a credit
analyst

• Assess the quality of various sources of information used by a credit
analyst

NO CHANGES


CR-3

2018

CR-3

2019

Giacomo De Laurentis, Renato Maino, and Luca Molteni,
Developing, Validating and Using Internal Ratings
(West Sussex, United Kingdom: John Wiley & Sons, 2010).

Chapter 2. Classifications and Key Concepts of Credit Risk

Giacomo De Laurentis, Renato Maino, and Luca Molteni,
Developing, Validating and Using Internal Ratings
(West Sussex, United Kingdom: John Wiley & Sons, 2010).
Chapter 2. Classifications and Key Concepts of Credit Risk

• Describe the role of ratings in credit risk management.

• Describe the role of ratings in credit risk management.

• Describe classifications of credit risk and their correlation with
other financial risks.

• Describe classifications of credit risk and their correlation with
other financial risks.

• Define default risk, recovery risk, exposure risk and calculate
exposure at default.

• Define default risk, recovery risk, exposure risk and calculate
exposure at default.

• Explain expected loss, unexpected loss, VaR, and concentration risk,
and describe the differences among them.

• Explain expected loss, unexpected loss, VaR, and concentration risk,
and describe the differences among them.

• Evaluate the marginal contribution to portfolio unexpected loss.

• Evaluate the marginal contribution to portfolio unexpected loss.

• Define risk-adjusted pricing and determine risk-adjusted return on
risk-adjusted capital (RARORAC).

• Define risk-adjusted pricing and determine risk-adjusted return on
risk-adjusted capital (RARORAC).

NO CHANGES


CR-4

2018

CR-4

2019

Giacomo De Laurentis, Renato Maino, and Luca Molteni,
Developing, Validating and Using Internal Ratings
(West Sussex, United Kingdom: John Wiley & Sons, 2010).
Chapter 3. Ratings Assignment Methodologies

Giacomo De Laurentis, Renato Maino, and Luca Molteni,
Developing, Validating and Using Internal Ratings
(West Sussex, United Kingdom: John Wiley & Sons, 2010).
Chapter 3. Ratings Assignment Methodologies

• Explain the key features of a good rating system.
• Describe the experts-based approaches, statistical-based models,
and numerical approaches to predicting default.
• Describe a rating migration matrix and calculate the probability of
default, cumulative probability of default, marginal probability of
default, and annualized default rate.
• Describe rating agencies’ assignment methodologies for issue and
issuer ratings.
• Describe the relationship between borrower rating and probability
of default.
• Compare agencies’ ratings to internal experts-based rating systems.
• Distinguish between the structural approaches and the reducedform approaches to predicting default.
• Apply the Merton model to calculate default probability and the
distance to default and describe the limitations of using the Merton
model.
• Describe linear discriminant analysis (LDA), define the Z-score
and its usage, and apply LDA to classify a sample of firms by credit
quality.
• Describe the application of logistic regression model to estimate
default probability.
• Define and interpret cluster analysis and principal component
analysis.
• Describe the use of cash flow simulation model in assigning rating
and default probability, and explain the limitations of the model.
• Describe the application of heuristic approaches, numeric
approaches, and artificial neural network in modeling default risk
and define their strengths and weaknesses.
• Describe the role and management of qualitative information in
assessing probability of default.

• Explain the key features of a good rating system.
• Describe the experts-based approaches, statistical-based models,
and numerical approaches to predicting default.
• Describe a rating migration matrix and calculate the probability of
default, cumulative probability of default, marginal probability of
default, and annualized default rate.
• Describe rating agencies’ assignment methodologies for issue and
issuer ratings.
• Describe the relationship between borrower rating and probability
of default.
• Compare agencies’ ratings to internal experts-based rating systems.
• Distinguish between the structural approaches and the reducedform approaches to predicting default.
• Apply the Merton model to calculate default probability and the
distance to default and describe the limitations of using the Merton
model.
• Describe linear discriminant analysis (LDA), define the Z-score
and its usage, and apply LDA to classify a sample of firms by credit
quality.
• Describe the application of a logistic regression model to estimate
default probability.
• Define and interpret cluster analysis and principal component
analysis.
• Describe the use of a cash flow simulation model in assigning rating
and default probability, and explain the limitations of the model.
• Describe the application of heuristic approaches, numeric
approaches, and artificial neural networks in modeling default risk
and define their strengths and weaknesses.
• Describe the role and management of qualitative information in
assessing probability of default.

NO CHANGES


CR-5

2018

René Stulz, Risk Management & Derivatives
(Florence, KY: Thomson South-Western, 2002).
Chapter 18. Credit Risks and Credit Derivatives

CR-5

2019

René Stulz, Risk Management & Derivatives
(Florence, KY: Thomson South-Western, 2002).
Chapter 18. Credit Risks and Credit Derivatives

• Using the Merton model, calculate the value of a firm’s debt and
equity and the volatility of firm value.

• Using the Merton model, calculate the value of a firm’s debt and
equity and the volatility of firm value.

• Explain the relationship between credit spreads, time to maturity,
and interest rates.

• Explain the relationship between credit spreads, time to maturity,
and interest rates.

• Explain the differences between valuing senior and subordinated
debt using a contingent claim approach.

• Explain the differences between valuing senior and subordinated
debt using a contingent claim approach.

• Explain, from a contingent claim perspective, the impact of
stochastic interest rates on the valuation of risky bonds, equity, and
the risk of default.

• Explain, from a contingent claim perspective, the impact of
stochastic interest rates on the valuation of risky bonds, equity, and
the risk of default.

• Compare and contrast different approaches to credit risk
modeling, such as those related to the Merton model, CreditRisk+,
CreditMetrics, and the KMV model.

• Compare and contrast different approaches to credit risk
modeling, such as those related to the Merton model, CreditRisk+,
CreditMetrics, and the KMV model.

• Assess the credit risks of derivatives.

• Assess the credit risks of derivatives.

• Describe a credit derivative, credit default swap, and total return
swap.

• Describe a credit derivative, credit default swap, and total return
swap.

• Explain how to account for credit risk exposure in valuing a swap.

• Explain how to account for credit risk exposure in valuing a swap.

NO CHANGES


CR-6

2018

Allan Malz, Financial Risk Management:
Models, History, and Institutions
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 7. Spread Risk and Default Intensity Models

CR-6

2019

Allan Malz, Financial Risk Management:
Models, History, and Institutions
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 7. Spread Risk and Default Intensity Models

• Compare the different ways of representing credit spreads.

• Compare the different ways of representing credit spreads.

• Compute one credit spread given others when possible.

• Compute one credit spread given others when possible.

• Define and compute the Spread ‘01.

• Define and compute the Spread ‘01.

• Explain how default risk for a single company can be modeled as a
Bernoulli trial.

• Explain how default risk for a single company can be modeled as a
Bernoulli trial.

• Explain the relationship between exponential and Poisson
distributions.

• Explain the relationship between exponential and Poisson
distributions.

• Define the hazard rate and use it to define probability functions for
default time and conditional default probabilities.

• Define the hazard rate and use it to define probability functions for
default time and conditional default probabilities.

• Calculate the conditional default probability given the hazard rate.

• Calculate the conditional default probability given the hazard rate.

• Calculate risk-neutral default rates from spreads.

• Calculate risk-neutral default rates from spreads.

• Describe advantages of using the CDS market to estimate hazard
rates.

• Describe advantages of using the CDS market to estimate hazard
rates.

• Explain how a CDS spread can be used to derive a hazard rate curve.

• Explain how a CDS spread can be used to derive a hazard rate curve.

• Explain how the default distribution is affected by the sloping of the
spread curve.

• Explain how the default distribution is affected by the sloping of the
spread curve.

• Define spread risk and its measurement using the mark-to-market
and spread volatility

• Define spread risk and its measurement using the mark-to-market
and spread volatility

NO CHANGES

CR-7

2018

Allan Malz, Financial Risk Management: Models, History,
and Institutions (Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 8. Portfolio Credit Risk
(Sections 8.1, 8.2, 8.3 only)
• Define and calculate default correlation for credit portfolios.
• Identify drawbacks in using the correlation-based credit portfolio
framework.
• Assess the impact of correlation on a credit portfolio and its
Credit VaR.
• Describe the use of a single factor model to measure portfolio credit
risk, including the impact of correlation.

CR-7

2019

Allan Malz, Financial Risk Management: Models, History,
and Institutions (Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 8. Portfolio Credit Risk
(Sections 8.1, 8.2, 8.3 only)
! • NEW LOS: Define and calculate Credit VaR.
• Define and calculate default correlation for credit portfolios.
• Identify drawbacks in using the correlation-based credit portfolio
framework.
• Assess the impact of correlation on a credit portfolio and its

Credit VaR.

• Define and calculate Credit VaR.

• Describe the use of a single factor model to measure portfolio credit
risk, including the impact of correlation.

• Describe how Credit VaR can be calculated using a simulation of
joint defaults with a copula.

• Describe how Credit VaR can be calculated using a simulation of
joint defaults with a copula.


CR-8

2018
Allan Malz, Financial Risk Management:
Models, History, and Institutions
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 9. Structured Credit Risk

CR-8

2019
Allan Malz, Financial Risk Management:
Models, History, and Institutions
(Hoboken, NJ: John Wiley & Sons, 2011).
Chapter 9. Structured Credit Risk

• Describe common types of structured products.

• Describe common types of structured products.

• Describe tranching and the distribution of credit losses in a
securitization.

• Describe tranching and the distribution of credit losses in a
securitization.

• Describe a waterfall structure in a securitization.

• Describe a waterfall structure in a securitization.

• Identify the key participants in the securitization process, and
describe conflicts of interest that can arise in the process.

• Identify the key participants in the securitization process, and
describe conflicts of interest that can arise in the process.

• Compute and evaluate one or two iterations of interim cashflows in
a three tiered securitization structure.

• Compute and evaluate one or two iterations of interim cashflows in
a three tiered securitization structure.

• Describe a simulation approach to calculating credit losses for
different tranches in a securitization.

• Describe a simulation approach to calculating credit losses for

different tranches in a securitization.

• Explain how the default probabilities and default correlations affect
the credit risk in a securitization.

• Explain how the default probabilities and default correlations affect
the credit risk in a securitization.

• Explain how default sensitivities for tranches are measured.

• Explain how default sensitivities for tranches are measured.

• Describe risk factors that impact structured products.

• Describe risk factors that impact structured products.

• Define implied correlation and describe how it can be measured.

• Define implied correlation and describe how it can be measured.

• Identify the motivations for using structured credit products

• Identify the motivations for using structured credit products

NO CHANGES